Open AccessA simulation approach to determine statistical significance of species turnover peaks in a species‐rich tropical cloud forest
Author(s) -
Bach K.,
Kessler M.,
Gradstein S. R.
Publication year - 2007
Publication title -
diversity and distributions
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.918
H-Index - 118
eISSN - 1472-4642
pISSN - 1366-9516
DOI - 10.1111/j.1472-4642.2007.00357.x
Subject(s) - range (aeronautics) , cloud forest , ecology , taxon , epiphyte , species diversity , biology , macroecology , vegetation (pathology) , species distribution , altitude (triangle) , tropics , species richness , habitat , medicine , materials science , montane ecology , pathology , composite material , geometry , mathematics
Use of β‐diversity indices in the study of spatial distribution of species diversity is hampered by the difficulty of applying significance tests. To overcome this problem we used a simulation approach in a study of species turnover of ferns, aroids, bromeliads, and melastomes along an elevational gradient from 1700 m to 3400 m in a species‐rich tropical cloud forest of Bolivia. Three parameters of species turnover (number of upper/lower elevational species limits per elevational step, Wilson–Shmida similarity index between adjacent steps) were analysed. Significant species turnover limits were detected at 2000 (± 50) m and 3050 m, which roughly coincided with the elevational limits of the main vegetation types recognized in the study area. The taxon specificity of elevational distributions implies that no single plant group can be used as a reliable surrogate for overall plant diversity and that the response to future climate change will be taxon‐specific, potentially leading to the formation of plant communities lacking modern analogues. Mean elevational range size of plant species was 490 m (± 369). Elevational range sizes of terrestrial species were shorter than those of epiphytes. We conclude that our simulation approach provides an alternative approach for assessing the statistical significance of levels of species turnover along ecological gradient without the limitations imposed by traditional statistical approaches.